Hugging Face (Twitter)
RT @rohanpaul_ai: Wow. This is a HUGE 24-trillion-token web dataset with document-level metadata available on @huggingface
apache-2.0 license
- collected from Common Crawl
- each document is labeled with a 12-field taxonomy covering topic, page type, complexity, and quality .
- Labels are generated by EAI-Distill-0.5b, a 0.5B-parameter model fine-tuned on Qwen2.5-32B-Instruct outputs. It matches teacher quality within 3% agreement and preserves domain recall within 1pp .
- Simple SQL-style filters produce datasets competitive with specialist pipelines. Math is within 8% of SOTA, web code up 14.3%, STEM up 24.5%, and medical up 8.6% .
- Inference on 23.6 B documents required about 90k AMD MI300x GPU-hours.
RT @rohanpaul_ai: Wow. This is a HUGE 24-trillion-token web dataset with document-level metadata available on @huggingface
apache-2.0 license
- collected from Common Crawl
- each document is labeled with a 12-field taxonomy covering topic, page type, complexity, and quality .
- Labels are generated by EAI-Distill-0.5b, a 0.5B-parameter model fine-tuned on Qwen2.5-32B-Instruct outputs. It matches teacher quality within 3% agreement and preserves domain recall within 1pp .
- Simple SQL-style filters produce datasets competitive with specialist pipelines. Math is within 8% of SOTA, web code up 14.3%, STEM up 24.5%, and medical up 8.6% .
- Inference on 23.6 B documents required about 90k AMD MI300x GPU-hours.
Hugging Face (Twitter)
RT @ChujieZheng: Uploaded on July 25, GSPO is already the #1 most popular paper on @huggingface for July 🍻 https://twitter.com/ClementDelangue/status/1949934196148895799#m
RT @ChujieZheng: Uploaded on July 25, GSPO is already the #1 most popular paper on @huggingface for July 🍻 https://twitter.com/ClementDelangue/status/1949934196148895799#m
Hugging Face (Twitter)
RT @theMetaStoneAI: 🚀 Introducing XBai o4：a milestone in our 4th-generation open-source technology based on parallel test time scaling！
In its medium mode, XBai o4 now fully outperforms OpenAI−o3−mini.📈
🔗Open-source weights: https://huggingface.co/MetaStoneTec/XBai-o4✅
Github link: https://github.com/MetaStone-AI/XBai-o4
RT @theMetaStoneAI: 🚀 Introducing XBai o4：a milestone in our 4th-generation open-source technology based on parallel test time scaling！
In its medium mode, XBai o4 now fully outperforms OpenAI−o3−mini.📈
🔗Open-source weights: https://huggingface.co/MetaStoneTec/XBai-o4✅
Github link: https://github.com/MetaStone-AI/XBai-o4
Hugging Face (Twitter)
RT @HuggingPapers: StepFun just released Step-3 on Hugging Face!
It's a new 321B-parameter VLM that's "Large yet Affordable," co-designed for cost-effective decoding.
Achieves unprecedented efficiency, setting a new Pareto frontier for LLM inference.
RT @HuggingPapers: StepFun just released Step-3 on Hugging Face!
It's a new 321B-parameter VLM that's "Large yet Affordable," co-designed for cost-effective decoding.
Achieves unprecedented efficiency, setting a new Pareto frontier for LLM inference.
Hugging Face (Twitter)
RT @NielsRogge: StepFun quitely dropped a 321B parameter VLM on @huggingface.. trained on Hopper GPUs similar to DeepSeek except more efficient
@StepFun_ai is yet-another-Chinese AI player besides @deepseek_ai, @Alibaba_Qwen, @Kimi_Moonshot, @MiniMax__AI, @TencentHunyuan and @Zai_org https://twitter.com/HuggingPapers/status/1952038716488208409#m
RT @NielsRogge: StepFun quitely dropped a 321B parameter VLM on @huggingface.. trained on Hopper GPUs similar to DeepSeek except more efficient
@StepFun_ai is yet-another-Chinese AI player besides @deepseek_ai, @Alibaba_Qwen, @Kimi_Moonshot, @MiniMax__AI, @TencentHunyuan and @Zai_org https://twitter.com/HuggingPapers/status/1952038716488208409#m
Hugging Face (Twitter)
RT @HaihaoShen: 🥳Qwen3-Coder-30B-A3B INT4 & INT2 GGUF models are available now -
https://huggingface.co/Intel/Qwen3-Coder-30B-A3B-Instruct-int4-AutoRound
https://huggingface.co/Intel/Qwen3-Coder-30B-A3B-Instruct-gguf-q2ks-mixed-AutoRound
#intel #int4 #autoround #huggingface
RT @HaihaoShen: 🥳Qwen3-Coder-30B-A3B INT4 & INT2 GGUF models are available now -
https://huggingface.co/Intel/Qwen3-Coder-30B-A3B-Instruct-int4-AutoRound
https://huggingface.co/Intel/Qwen3-Coder-30B-A3B-Instruct-gguf-q2ks-mixed-AutoRound
#intel #int4 #autoround #huggingface
huggingface.co
Intel/Qwen3-Coder-30B-A3B-Instruct-int4-AutoRound · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Hugging Face (Twitter)
RT @Alibaba_Qwen: 🚀 Meet Qwen-Image — a 20B MMDiT model for next-gen text-to-image generation. Especially strong at creating stunning graphic posters with native text. Now open-source.
🔍 Key Highlights:
🔹 SOTA text rendering — rivals GPT-4o in English, best-in-class for Chinese
🔹 In-pixel text generation — no overlays, fully integrated
🔹 Bilingual support, diverse fonts, complex layouts
🎨 Also excels at general image generation — from photorealistic to anime, impressionist to minimalist. A true creative powerhouse.
Blog:https://qwenlm.github.io/blog/qwen-image/
Hugging Face：https://huggingface.co/Qwen/Qwen-Image
ModelScope：https://modelscope.cn/models/Qwen/Qwen-Image
Github：github.com/QwenLM/Qwen-Image
Technical report：https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/Qwen_Image.pdf
Demo: https://modelscope.cn/aigc/imageGeneration?tab=advanced
RT @Alibaba_Qwen: 🚀 Meet Qwen-Image — a 20B MMDiT model for next-gen text-to-image generation. Especially strong at creating stunning graphic posters with native text. Now open-source.
🔍 Key Highlights:
🔹 SOTA text rendering — rivals GPT-4o in English, best-in-class for Chinese
🔹 In-pixel text generation — no overlays, fully integrated
🔹 Bilingual support, diverse fonts, complex layouts
🎨 Also excels at general image generation — from photorealistic to anime, impressionist to minimalist. A true creative powerhouse.
Blog:https://qwenlm.github.io/blog/qwen-image/
Hugging Face：https://huggingface.co/Qwen/Qwen-Image
ModelScope：https://modelscope.cn/models/Qwen/Qwen-Image
Github：github.com/QwenLM/Qwen-Image
Technical report：https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/Qwen_Image.pdf
Demo: https://modelscope.cn/aigc/imageGeneration?tab=advanced
Hugging Face (Twitter)
RT @_fracapuano: We shipped @LeRobotHF to its first major release, on Pypi and GitHub.
Alongside the team at @huggingface we’re making robotics more accessible, collaborative, and we hope this release makes contributing easier and better.
Links in 🧵
RT @_fracapuano: We shipped @LeRobotHF to its first major release, on Pypi and GitHub.
Alongside the team at @huggingface we’re making robotics more accessible, collaborative, and we hope this release makes contributing easier and better.
Links in 🧵
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Hugging Face (Twitter)
RT @jandotai: Hugging Face 🤝 Jan
You can now use Hugging Face as a remote model provider in Jan.
Go to Settings -> Model Providers -> add your Hugging Face API key. Then open a new chat and pick a model from @huggingface.
Works with any model in Hugging Face in Jan.
RT @jandotai: Hugging Face 🤝 Jan
You can now use Hugging Face as a remote model provider in Jan.
Go to Settings -> Model Providers -> add your Hugging Face API key. Then open a new chat and pick a model from @huggingface.
Works with any model in Hugging Face in Jan.
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Hugging Face (Twitter)
RT @abidlabs: New Gradio component: 🥳 gr.Dialogue:
• As an output, it can be used to show diarized speech transcription
• As input, it's perfect for multispeaker TTS models, as it also supports auto-complete tags 🪄
Try it out in Gradio 5.40!
RT @abidlabs: New Gradio component: 🥳 gr.Dialogue:
• As an output, it can be used to show diarized speech transcription
• As input, it's perfect for multispeaker TTS models, as it also supports auto-complete tags 🪄
Try it out in Gradio 5.40!
Hugging Face (Twitter)
RT @jackvial89: I've created a @LeRobotHF @huggingface dataset for the screwdriver robot. This dataset contains 391 human demonstrations of attaching a part with a screw in 3 positions: left, right, center. Currently training a few different models on this dataset!
RT @jackvial89: I've created a @LeRobotHF @huggingface dataset for the screwdriver robot. This dataset contains 391 human demonstrations of attaching a part with a screw in 3 positions: left, right, center. Currently training a few different models on this dataset!
Hugging Face (Twitter)
RT @RisingSayak: Wait is over 🤯
An Apache 2.0 DiT-based image generation model from @Alibaba_Qwen -- Qwen-Image 🔥
Supported in Diffusers. Training script PR is up and should be merged soon.
Go, fire!
RT @RisingSayak: Wait is over 🤯
An Apache 2.0 DiT-based image generation model from @Alibaba_Qwen -- Qwen-Image 🔥
Supported in Diffusers. Training script PR is up and should be merged soon.
Go, fire!
Hugging Face (Twitter)
RT @_lewtun: One line of code is all it takes to fine-tune the gpt-oss models from @OpenAI 🔥
> Support to target the MoE expert layers with PEFT
> Kernels for FlashAttention3 & MegaBlocks
> Fast inference with MXFP4 quantization format
In our testing, these models are extremely efficient to tune and can be adapted to new domains with just a few 100 samples 🤯
Download the models: huggingface.co/openai
Training & inference recipes: https://github.com/huggingface/gpt-oss-recipes/tree/main
RT @_lewtun: One line of code is all it takes to fine-tune the gpt-oss models from @OpenAI 🔥
> Support to target the MoE expert layers with PEFT
> Kernels for FlashAttention3 & MegaBlocks
> Fast inference with MXFP4 quantization format
In our testing, these models are extremely efficient to tune and can be adapted to new domains with just a few 100 samples 🤯
Download the models: huggingface.co/openai
Training & inference recipes: https://github.com/huggingface/gpt-oss-recipes/tree/main
Hugging Face (Twitter)
RT @mervenoyann: gpt-oss @OpenAI is here! 🔥
> two MoEs with 21B/3.6B and 117B/5.1B total/active params, efficient reasoning models 🤯
> use & fine-tune with transformers & TRL 🛠️
> inference powered by @huggingface Inference Providers 🫡
> apache 2.0 license 💗
RT @mervenoyann: gpt-oss @OpenAI is here! 🔥
> two MoEs with 21B/3.6B and 117B/5.1B total/active params, efficient reasoning models 🤯
> use & fine-tune with transformers & TRL 🛠️
> inference powered by @huggingface Inference Providers 🫡
> apache 2.0 license 💗